Radar-based place recognition.
Radar-based place recognition using learned descriptors is relatively unexplored area.
In [1]} authors adapt a hand-crafted ScanContext [2]} descriptor, originally used for point cloud-based place recognition.
 [3]} presents a learned a global descriptor computed using convolutional neural network with NetVLAD [4]} aggregation layer, commonly used in visual domain. In order to achieve rotational invariance authors introduce couple of modifications, such as cylindrical convolutions, anti-aliasing blurring, and azimuth-wise max-pooling.
[5]} extends this method by developing a two-stage approach which integrates global descriptor learning with precise pose estimation using spectral landmark-based techniques.
